Stakeholder engagement in methodological research: Development of a clinical decision support tool

Denise H Daudelin; Robin Ruthazer; Manlik Kwong; Rebecca C Lorenzana; Daniel J Hannon; David M Kent; Timothy E McAlindon; Norma Terrin; John B Wong; Harry P Selker

doi:10.1017/cts.2019.443

Stakeholder engagement in methodological research: Development of a clinical decision support tool

J Clin Transl Sci. 2020 Feb 18;4(2):133-140. doi: 10.1017/cts.2019.443. eCollection 2020 Apr.

Authors

Denise H Daudelin^{1

2}, Robin Ruthazer^{1

2}, Manlik Kwong^{1

2}, Rebecca C Lorenzana¹, Daniel J Hannon³, David M Kent⁴, Timothy E McAlindon⁵, Norma Terrin^{1

2}, John B Wong^{1

2

6}, Harry P Selker^{1

2}

Affiliations

¹ Tufts Clinical and Translational Science Institute, Tufts University, Boston, MA, USA.
² Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA.
³ School of Engineering, Tufts University, Medford, MA, USA.
⁴ Predictive Analytics and Comparative Effectiveness (PACE) Center, Institute for Clinical Research and Health Policy Studies (ICRHPS), Tufts Medical Center, Boston, MA, USA.
⁵ Division of Rheumatology, Tufts Medical Center, Boston, MA, USA.
⁶ Division of Clinical Decision Making, Tufts Medical Center, Boston, MA, USA.

Abstract

Introduction: Shared patient-clinician decision-making is central to choosing between medical treatments. Decision support tools can have an important role to play in these decisions. We developed a decision support tool for deciding between nonsurgical treatment and surgical total knee replacement for patients with severe knee osteoarthritis. The tool aims to provide likely outcomes of alternative treatments based on predictive models using patient-specific characteristics. To make those models relevant to patients with knee osteoarthritis and their clinicians, we involved patients, family members, patient advocates, clinicians, and researchers as stakeholders in creating the models.

Methods: Stakeholders were recruited through local arthritis research, advocacy, and clinical organizations. After being provided with brief methodological education sessions, stakeholder views were solicited through quarterly patient or clinician stakeholder panel meetings and incorporated into all aspects of the project.

Results: Participating in each aspect of the research from determining the outcomes of interest to providing input on the design of the user interface displaying outcome predications, 86% (12/14) of stakeholders remained engaged throughout the project. Stakeholder engagement ensured that the prediction models that form the basis of the Knee Osteoarthritis Mathematical Equipoise Tool and its user interface were relevant for patient-clinician shared decision-making.

Conclusions: Methodological research has the opportunity to benefit from stakeholder engagement by ensuring that the perspectives of those most impacted by the results are involved in study design and conduct. While additional planning and investments in maintaining stakeholder knowledge and trust may be needed, they are offset by the valuable insights gained.

Keywords: Stakeholder engagement; decision support; knee osteoarthritis; predictive models; shared decision-making; total knee replacement.

Abstract

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